National analysis of lung cancer data: overview
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1 National analysis of lung cancer data: overview Henrik Møller, Sharma Riaz and Margreet Lüchtenborg Thames Cancer Registry, King s College London National Cancer Intelligence Network (UK) 1
2 Cancer intelligence lead areas Thames Cancer Registry: Lung cancer (Sharma Riaz, Margreet Lüchtenborg) Upper gastrointestinal cancer (Vicki Coupland, Julie Confortion) Build of the national cancer data repository National lead for analysis and research (Henrik Møller) 2
3 The lung cancer work programme Examples of completed work (5) Examples of ongoing work (2) Workprogramme List of outputs Report to NCIN Workprogramme
4 Examples of completed work Trends in mesothelioma survival Lung cancer incidence in relation to urbanisation Trends in small-cell lung cancer incidence Completeness of case ascertainment Variation in radical resection and survival 4
5 (1) One-year survival in mesothelioma Period (mid-year of group) Male Female 5
6 ASR(E) ASR(E) (2) Lung cancer incidence in relation to urbanisation and deprivation Affluent (1) Deprived (5) 0 Affluent (1) Deprived (5) Socio-economic deprivation Socio-economic deprivation Rural Urban Rural Urban Males Females 6
7 ASR(E) ASR(E) ASR(E) (3) Trends in incidence of SCLC and all LC A All lung cancer B All lung cancer Period (mid-year of group) Cohort of birth (mid-year of group) Male Female Male Female C 14 Small cell lung cancer D 14 Small cell lung cancer Period (mid-year of group) Male Female Cohort of birth (mid-year of group) Male Female 7
8 PCT of residence Proportion of lung cases having a pneumonectomy (%) Q1 Q2 Q3 Q4 Q5 (4) Radical resection in NSC lung cancer
9 Hazard ratio Radical resection (%) and survival in regions 1.05 SE 1.00 EE SW NE NW Y&H EM 0.95 WM 0.90 L Radical surgery (%) Hazard ratio 95% CI Radical surgery 95% CI 9
10 (5) Errors in cancer survival estimation Incomplete case ascertainment likely to bias survival estimates because good-prognosis cases are missed Bullard 2000; Robinson 2007, 2010 Death-certificate initiated registration likely to create too low survival times if hospital activity in relation to recurrence or death is mistaken for the initial diagnosis Møller 2010 (1) and (2) leads to artificially low survival estimates 10
11 11
12 Data and methods Record linkage study using cancer registrations and HES records, HES-only cases who had surgical treatment represent possibly missed good-prognosis cases For apparently rapid fatal cases (1Y): identify earliest cancer record in HES Compute alternative one-year survival estimate 12
13 Completeness of lung cancer case ascertainment in cancer registries in England, Lung cancer HESO REPO H/R % Total Sex Male Female NA 0 0 Registry EASTERN NORTH WEST NORTHERN & YORKSHIRE OXFORD SOUTH WEST THAMES TRENT WEST MIDLANDS NA 7 0 HESO: HES-only records from the repository with a code for "major surgery". REPO: Valid cancer registratons from the linked repository. These exclude the HESO records. 13
14 Survival time error Date of HES diagnosis Date of diagnosis (CR) Death 14
15 Cumulative percentage of registrations 100% 95% Difference in survival time between registry and HES derived survival Lung cancer % 90% 85% EASTERN CANCER REGISTRATION & INFORMATION CENTRE (ECRIC) NORTH WEST CANCER INTELLIGENCE SERVICE 80% 75% 70% 65% 60% NORTHERN & YORKSHIRE CANCER REGISTRY & INFORMATION SERVICE OXFORD CANCER INTELLIGENCE UNIT SOUTH WEST CANCER INTELLIGENCE SERVICE THAMES CANCER REGISTRY TRENT CANCER REGISTRY WEST MIDLANDS CANCER INTELLIGENCE UNIT 55% 50% day registry survivors = Additional survival time in days 15
16 Conclusion Completeness of lung cancer case ascertainment in English cancer registries is high: around 99.6% Survival time error is low: around 0.4% 1Y fatal lung cancer cases are misclassified over the one-year time point One-year lung cancer survival estimates may be underestimated by up to 0.8 percentage points (24.5 to 25.3) 16
17 Examples of ongoing work Lung cancer survival in five countries Lung cancer survival in relation to peer-review measures 17
18
19
20 Extension to five countries, England, Norway, Sweden, Netherlands and Denmark Can survival differences be attributed to Stage distribution? Treatment patterns? 20
21 21
22 (2) Lung cancer peer review Each provider unit obtained an overall compliance score 4 groups of scores 32 individual scores (eg specialist surgeon in MDT) Are peer review scores associated with survival? 22
23 Acknowledgment This paper is a contribution from the National Cancer Intelligence Network ( and is based on the information collected and quality assured by the regional cancer registries in England ( 23
24 24
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